1. Field of the Invention
The present invention relates to noise reduction technology that reduces noise by performing temporal filtering on a video image signal of a moving image captured by a digital video camera, or the like, and to a noise reduction apparatus and a noise reduction method to which the noise reduction technology is applied.
2. Description of the Related Art
Conventionally, various noise reduction methods have been developed in order to improve the image quality of image capture devices. Video noise reduction technology is broadly divided into spatial filter-type noise reduction that performs spatial filtering and temporal filter-type noise reduction that performs temporal filtering.
Temporal filter-type noise reduction has an advantage that noise can be reduced while maintaining resolution, because spatial frequency components of a video image ideally do not deteriorate. With regard to temporal filter-type noise reduction, many techniques for switching processing in accordance with an object or upstream image processing have been proposed.
In Japanese Patent Laid-Open No. 2003-333370, temporal filter-type noise reduction that suppresses deterioration due to motion blur that occurs in a case when an object is moving has been proposed. In order to avoid deterioration due to blur deterioration, noise reduction is switched in accordance with the motion vector of an object.
In Japanese Patent Laid-Open No. 2010-147774, a coefficient of temporal noise reduction is changed so that noise variance is constant, in accordance with upstream frame rate conversion processing of noise reduction processing.
With the conventional techniques described in Japanese Patent Laid-Open No. 2003-333370 and Japanese Patent Laid-Open No. 2010-147774, there is a problem in that, although adaptive noise reduction is performed on an object or image processing, variance of the noise itself is not taken into consideration. With regard to moving image noise, temporal variance of the noise itself is a significant factor determining the perceived amount of noise. For example, if a 24 fps moving image with noise is compared with each frame viewed as a still image, the variance of noise will be more noticeable in the moving image, and thus, the noise is strongly perceived. In this manner, even in a case when signals have the same amount of noise, if temporal characteristics of noise, such as the changing temporal frequency of noise, for example, are different, the amount of noise that a person perceives will also differ greatly. This is because human vision has the band-pass type qualities of being highly sensitive to variance of 5 to 10 Hz, but having substantially zero sensitivity when variance is greater than or equal to 60 Hz.
The temporal characteristics of noise depend on image capture conditions, such as ISO sensitivity, the temperature of the image sensor, and the like, and thus, differ for each image capture. Accordingly, even if the motion of an object or upstream image processing is the same, if the temporal characteristics of the noise itself are different, it is necessary to switch the noise reduction processing.